{"id":"W2576982189","doi":"10.1016/j.ebiom.2017.02.022","title":"Mining Human Prostate Cancer Datasets: The “camcAPP” Shiny App","year":2017,"lang":"en","type":"article","venue":"EBioMedicine","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto","funders":"Academy of Medical Sciences; National Institute for Health and Care Research; Cancer Research UK","keywords":"Prostate cancer; Computer science; Prostatectomy; Annotation; Relevance (law); Cancer; Information retrieval; Bioinformatics; Medicine; Artificial intelligence; Biology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003172025,0.00237254,0.001671136,0.005278289,0.0007610266,0.003034339,0.003547294,0.002122998,0.06718183],"category_scores_gemma":[0.01254829,0.00113341,0.002423204,0.005078025,0.0005394853,0.002414709,0.006228094,0.002458978,0.03268031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006337696,"about_ca_system_score_gemma":0.001406397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003097361,"about_ca_topic_score_gemma":0.007584204,"domain_scores_codex":[0.9984622,0.000333205,0.0001671738,0.0003817962,0.0005744947,0.00008106067],"domain_scores_gemma":[0.9951789,0.003115976,0.0002868003,0.000742745,0.0003701138,0.00030532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003653927,0.00005762295,0.001376632,0.002880589,0.0003742707,0.0006425173,0.0003271294,0.0006774609,0.001620318,0.002073659,0.9267643,0.06284007],"study_design_scores_gemma":[0.0006296457,0.0001558288,0.0095144,0.001491182,0.0002156937,0.001658482,0.0005201477,0.01597079,0.006065687,0.02579373,0.9377548,0.0002296446],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.004056306,0.006756367,0.05826527,0.004121878,0.001026188,0.00106943,0.6184487,0.2910149,0.01524099],"genre_scores_gemma":[0.0358331,0.004989292,0.2216185,0.004924881,0.0007522053,0.00639649,0.67788,0.03494323,0.0126623],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06718183,"threshold_uncertainty_score":0.2247456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05564053333025964,"score_gpt":0.4103770028042905,"score_spread":0.3547364694740308,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}